J. Aggarwal and M. S. Ryoo, Human activity analysis, ACM Computing Surveys, vol.43, issue.3, p.16, 2011.
DOI : 10.1145/1922649.1922653

D. P. Chau, F. Bremond, and M. Thonnat, A multi-feature tracking algorithm enabling adaptation to context variations, 4th International Conference on Imaging for Crime Detection and Prevention 2011 (ICDP 2011), 2004.
DOI : 10.1049/ic.2011.0127
URL : https://hal.archives-ouvertes.fr/inria-00632245

N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.886-893, 2003.
DOI : 10.1109/CVPR.2005.177
URL : https://hal.archives-ouvertes.fr/inria-00548512

H. M. Dee, A. G. Cohn, and D. C. Hogg, Building semantic scene models from unconstrained video, Computer Vision and Image Understanding, vol.116, issue.3, pp.446-456, 2012.
DOI : 10.1016/j.cviu.2011.09.005

W. Hu, X. Xiao, Z. Fu, D. Xie, T. Tan et al., A system for learning statistical motion patterns, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.9 2, pp.1450-1464, 2006.

A. Karakostas, A. Briassouli, K. Avgerinakis, I. Kompatsiaris, and T. M. , The dem@care experiments and datasets: a technical report, 2014.

I. Laptev and T. Lindeberg, Space-time interest points, ICCV, pp.432-439, 2003.

I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld, Learning realistic human actions from movies, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587756
URL : https://hal.archives-ouvertes.fr/inria-00548659

A. Nghiem, E. Auvinet, and J. Meunier, Head detection using kinect camera and its application to fall detection, ISSPA, pp.164-169, 2012.

H. Wang, A. Kläser, C. Schmid, and C. Liu, Action recognition by dense trajectories, CVPR 2011, pp.3169-3176, 2005.
DOI : 10.1109/CVPR.2011.5995407
URL : https://hal.archives-ouvertes.fr/inria-00583818

H. Wang and C. Schmid, Action Recognition with Improved Trajectories, 2013 IEEE International Conference on Computer Vision, pp.3551-3558, 2004.
DOI : 10.1109/ICCV.2013.441
URL : https://hal.archives-ouvertes.fr/hal-00873267